/**
* Copyright (c) 2025 Huawei Technologies Co., Ltd.
* This program is free software, you can redistribute it and/or modify it under the terms and conditions of
* CANN Open Software License Agreement Version 2.0 (the "License").
* Please refer to the License for details. You may not use this file except in compliance with the License.
* THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED,
* INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE.
* See LICENSE in the root of the software repository for the full text of the License.
*/

/*!
 * \file xor.h
 * \brief
 */
#ifndef LIB_MATH_XOR_H
#define LIB_MATH_XOR_H

#include "kernel_tensor.h"
#include "kernel_operator_intf.h"
#include "kernel_pop_stack_buffer.h"
#include "../../../impl/adv_api/detail/math/xor/xor_common_impl.h"
#if ASCENDC_CPU_DEBUG
#include "kernel_log.h"
#include <type_traits>
#endif

#if (defined(__CCE_AICORE__) && (__CCE_AICORE__ == 200 || __CCE_AICORE__ == 220 || __CCE_AICORE__ == 300)) || \
    defined(__DAV_C310__) || defined(__DAV_310R6__) || (__NPU_ARCH__ == 5102)
namespace AscendC {
#pragma begin_pipe(V)
/*
 * @brief Xor Computes the element-wise logical XOR of the given input tensors. Zeros are treated as False and nonzeros
 * are treated as True. Mathematical formulas: 0^0=0；0^1=1；1^0=1；1^1=0
 * @ingroup xor
 * @param [out] dstTensor, output LocalTensor
 * @param [in] srcTensor0, input LocalTensor
 * @param [in] srcTensor1, input LocalTensor
 * @param [in] sharedTmpBuffer, input local temporary Tensor
 * @param [in] calCount, amount of input data to be calculated
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Xor(const LocalTensor<T>& dstTensor, const LocalTensor<T>& src0Tensor,
    const LocalTensor<T>& src1Tensor, const LocalTensor<uint8_t>& sharedTmpBuffer, const uint32_t calCount)
{
    // Only for AI Vector Core.
    if ASCEND_IS_AIC {
        return;
    }
    static_assert((std::is_same<T, int16_t>::value || std::is_same<T, uint16_t>::value),
        "Failed to check the data types, current api support data types are int16_t/uint16_t.");

    XorImpl<T, isReuseSource>(dstTensor, src0Tensor, src1Tensor, sharedTmpBuffer, calCount);
}
/*
 * @brief Xor Computes the element-wise logical XOR of the given input tensors. Zeros are treated as False and nonzeros
 * are treated as True. Mathematical formulas: 0^0=0；0^1=1；1^0=1；1^1=0
 * @ingroup xor
 * @param [out] dstTensor, output LocalTensor
 * @param [in] srcTensor0, input LocalTensor
 * @param [in] srcTensor1, input LocalTensor
 * @param [in] sharedTmpBuffer, input local temporary Tensor
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Xor(const LocalTensor<T>& dstTensor, const LocalTensor<T> &src0Tensor,
    const LocalTensor<T> &src1Tensor, const LocalTensor<uint8_t>& sharedTmpBuffer)
{
#if defined(ASCENDC_CPU_DEBUG) && (ASCENDC_CPU_DEBUG == 1)
    bool result = (src0Tensor.GetSize() == src1Tensor.GetSize());
    ASCENDC_ASSERT(result, { KERNEL_LOG(KERNEL_ERROR,
        "Failed to check src0Tensor size %u and src1Tensor size %u, "
        "should be equal When calCount parameter is not included.", src0Tensor.GetSize(), src1Tensor.GetSize()); });
#endif
    Xor<T, isReuseSource>(dstTensor, src0Tensor, src1Tensor, sharedTmpBuffer, src0Tensor.GetSize());
}

/*
 * @brief Xor Computes the element-wise logical XOR of the given input tensors. Zeros are treated as False and nonzeros
 * are treated as True. Mathematical formulas: 0^0=0；0^1=1；1^0=1；1^1=0
 * @ingroup xor
 * @param [out] dstTensor, output LocalTensor
 * @param [in] srcTensor0, input LocalTensor
 * @param [in] srcTensor1, input LocalTensor
 * @param [in] calCount, amount of input data to be calculated
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Xor(const LocalTensor<T> &dstTensor, const LocalTensor<T> &src0Tensor,
    const LocalTensor<T> &src1Tensor, const uint32_t calCount)
{
    LocalTensor<uint8_t> sharedTmpBuffer;
    bool ans = PopStackBuffer<uint8_t, TPosition::LCM>(sharedTmpBuffer);
    ASCENDC_ASSERT((ans), { KERNEL_LOG(KERNEL_ERROR, "PopStackBuffer Error!"); });

    Xor<T, isReuseSource>(dstTensor, src0Tensor, src1Tensor, sharedTmpBuffer, calCount);
}

/*
 * @brief Xor Computes the element-wise logical XOR of the given input tensors. Zeros are treated as False and nonzeros
 * are treated as True. Mathematical formulas: 0^0=0；0^1=1；1^0=1；1^1=0
 * @ingroup xor
 * @param [out] dstTensor, output LocalTensor
 * @param [in] srcTensor0, input LocalTensor
 * @param [in] srcTensor1, input LocalTensor
 */
template <typename T, bool isReuseSource = false>
__aicore__ inline void Xor(const LocalTensor<T> &dstTensor, const LocalTensor<T> &src0Tensor,
    const LocalTensor<T> &src1Tensor)
{
#if defined(ASCENDC_CPU_DEBUG) && (ASCENDC_CPU_DEBUG == 1)
    bool result = (src0Tensor.GetSize() == src1Tensor.GetSize());
    ASCENDC_ASSERT(result, { KERNEL_LOG(KERNEL_ERROR,
        "Failed to check src0Tensor size %u and src1Tensor size %u, "
        "should be equal When calCount parameter is not included.", src0Tensor.GetSize(), src1Tensor.GetSize()); });
#endif
    Xor<T, isReuseSource>(dstTensor, src0Tensor, src1Tensor, src0Tensor.GetSize());
}
#pragma end_pipe
}  // namespace AscendC
#endif
#endif  // LIB_MATH_XOR_H
